Nutrition and the transplant candidate
Bibliographic record
Abstract
Cirrhosis is the most common indication for liver transplantation (LT) worldwide. Malnutrition is present in at least two-thirds of patients with cirrhosis awaiting LT. It negatively impacts survival, quality of life, and the ability to respond to stressors, such as infection and surgery. Muscle wasting or sarcopenia is the most objective feature of chronic protein malnutrition in cirrhosis, and this condition is associated with increased morbidity and mortality before and after LT. In addition to its objectivity, muscularity assessment with cross-sectional imaging studies is a useful marker of nutritional status in LT candidates, as sarcopenia reflects a chronic decline in the general physical condition, rather than acute severity of the liver disease. Despite the high prevalence and important prognostic role, malnutrition and sarcopenia are frequently overlooked because standards for nutritional assessment are lacking and challenges such as fluid retention and obesity are prevalent. In this review, current diagnostic methods to evaluate malnutrition, including muscle abnormalities in cirrhosis, are discussed and current knowledge regarding the incidence and clinical impact of malnutrition in cirrhosis and its impact after LT are presented. Existing and potential novel therapeutic strategies for malnutrition in cirrhosis are also discussed, emphasizing the treatment of muscle wasting in the LT candidate in an effort to improve survival while waiting for LT and to reduce morbidity and mortality after LT.Liver Transplantation 23 1451-1464 2017 AASLD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".